• info@sease.io
  • +44 7868649253

We are what you are searching for! Hire Us

Twitter Linkedin-in Github Youtube
Sease
  • About us
    • Research & Development
    • Our Team
    • Our Clients
    • Partner
    • Conferences attended
    • Next Events
    • Careers
  • Consulting
  • Training
    • Apache Solr Training
    • Elasticsearch Training
    • Search Relevance Training
    • Learning To Rank Training
    • Search Quality Evaluation Training
    • Artificial Intelligence in Search
    • Mini Training
  • Open Source
  • Blog
    • Blog News
    • Main Blog
    • Tips and Tricks
  • Contacts
    • Newsletter
Sease
  • About us
    • Research & Development
    • Our Team
    • Our Clients
    • Partner
    • Conferences attended
    • Next Events
    • Careers
  • Consulting
  • Training
    • Apache Solr Training
    • Elasticsearch Training
    • Search Relevance Training
    • Learning To Rank Training
    • Search Quality Evaluation Training
    • Artificial Intelligence in Search
    • Mini Training
  • Open Source
  • Blog
    • Blog News
    • Main Blog
    • Tips and Tricks
  • Contacts
    • Newsletter

Category: Main Blog

  • Home
  • Blog
  • Main Blog
Learning To Rank Main Blog
The Importance of Online Testing in Learning to Rank
_ Anna Ruggero

The Importance of Online Testing in Learning to Rank – Part 1

It is fundamental to online test your Learning To Rank system, this blog shows you how it can be implemented and the most common mistakes.

READ MORE ♥53
Apache Solr Main Blog
docvalues vs stored fields
_ Elia Porciani

DocValues VS Stored Fields : Apache Solr Features and Performance SmackDown

This blog post aims to give a better understanding of Docvalues and stored fields in Apache Solr for the operations in which they can be used interchangeably.

READ MORE ♥79
Apache Lucene Apache Solr Main Blog
weighted synonyms
_ Alessandro Benedetti

Introducing Weighted Synonyms in Apache Lucene/Solr

This blog post is about our latest contribution to the Apache Lucene project: introducing weighted synonyms to provide better query expansion.

READ MORE ♥70
Main Blog Music Information Retrieval
music information retrieval
_ Andrea Gazzarini

Music Information Retrieval: the Intervals Table

In this post we describe what is an Intervals Table and how to build it using a Behaviour-Driven-Development (BDD) approach.

READ MORE ♥26
Apache Solr Main Blog
apache solr atomic updates
_ Andrea Gazzarini

Apache Solr Atomic Updates: a Polymorphic Approach

In this post we describe an approach to solve the problem of an application that requires both Full and Atomic Updates, using one of the powerful concepts in Object Oriented Programming: Polymorphism.

READ MORE ♥61
Main Blog search quality evaluation
_ Alessandro Benedetti

Road to Rated Ranking Evaluator Enterprise

It was the spring of 2018, Andrea was strenuously working on a customer project, continuously tuning search configurations and checking the ground truth for certain queries manually. That was pretty much the standard at the time, the brilliant Quepid[1] from our friends at Open Source Connection helped in some use cases, but there was nothing…

READ MORE ♥40
Entity Search Main Blog
Entity Search with Graph Embeddings 4
_ Anna Ruggero

Entity Search with graph embeddings – Part 4 – Evaluation and conclusion

In this final part of the Entity Search with Graph Embeddings serie we see evaluation measures and results.

READ MORE ♥32
Entity Search Main Blog
entity search graph embeddings 3
_ Anna Ruggero

Entity Search with Graph Embeddings – Part 3 – Documents and Retrieval

Third part of the journey into Entity Search trough embeddings. Focus of the post is the ranking phase.

READ MORE ♥25
Entity Search Main Blog
entity search graph embedd 2
_ Anna Ruggero

Entity Search with graph embeddings – Part 2 – Embeddings and clustering

In this blog post we continue our journey into Entity Search with graph embeddings. In part 2 we talk about embeddings and clustering.

READ MORE ♥24
Entity Search Main Blog
entity search with graph embeddings
_ Anna Ruggero

Entity Search with graph embeddings – Part 1 – Overview

Entity Search: how to build virtual documents leveraging on graph embeddings. How to exploit entity embeddings and clustering.

READ MORE ♥35
  • 1
  • 2
  • 3
  • 4
  • 5
Are you looking for something in particular?
Recent Posts
  • Sease at Berlin Buzzwords 2022
    May 20, 2022
  • Have Neural Networks Killed the Inverted Index
    Have Neural Networks Killed the Inverted Index?
    April 28, 2022
  • QueryResultCache and FilterCache in Apache Solr
    QueryResultCache and FilterCache in Apache Solr
    April 14, 2022
Upcoming Events
  1. Beginner Elasticsearch

    June 13 @ 3:00 pm - June 15 @ 7:00 pm
  2. Neural Search Comes to Apache Solr [Berlin Buzzwords]

    June 13 @ 4:00 pm - 4:40 pm
  3. Word2Vec model to generate synonyms on the fly in Apache Lucene [Berlin Buzzwords]

    June 14 @ 2:50 pm - 3:30 pm

View All Events

Sease Ltd.

International House
776-778 Barking Road
BARKING London
E13 9PJ

Quick Links
  • Privacy Policy
  • Cookie Policy
  • Newsletter
  • Contacts
Services
  • Consulting
  • Training
  • Open Source
Subscribe

Follow our newsletter to stay
updated.

Apache Lucene, Apache Solr, Apache Stanbol, Apache ManifoldCF, Apache OpenNLP and their respective logos are trademarks of the Apache Software Foundation.
Elasticsearch is a trademark of Elasticsearch BV, registered in the U.S. and in other countries.
OpenSearch is a registered trademark of Amazon Web Services.
Vespa is a registered trademark of Yahoo.

Copyright © 2016-2022 Sease Ltd. All rights reserved.

 

Loading Comments...